An analysis of integrated robust hybrid model for third-party reverse logistics partner selection under fuzzy environment

Chandra Prakash and M.K. Barua

Resources, Conservation & Recycling, 2016, vol. 108, issue C, 63-81

Abstract: Owing to environmental and waste disposal issues, enforced legislation and corporate social concern; companies are focusing on reverse logistics (RL) practices, especially in the present scenario dominated by intense competition, demanding customer and fast changing technologies. These practices are widely adopted by industries through reverse logistics partners. However, the evaluation and selection of the reverse logistics partner is a matter of concern which needs a very grave decision, involving complexity due to presence of numerous associated factors. In addition, it is hypothesized that the decision makers might be inconsistent to some extent in their views and preferences that affect other dominant constituents. Consequently, incomplete and inadequate sort of information may occur among various selection criteria, which is termed ‘multi-criteria decision making’ (MCDM) problem. The goal of the present study is to discuss an integrated model based on fuzzy analytic hierarchy process (FAHP) for evaluation and prioritization of selection criteria and fuzzy technique for order performance by similarity to ideal solution (FTOPSIS) for the selection and development of reverse logistics partner. This study is an attempt to present a genuine concern of Indian electronics industry using an integrated approach to demonstrate the application of the proposed framework as well. In this study two stage sensitivity analyses are performed to get further insight of evaluation and selection of RL partner and verification of robustness of the model. This study aims to provide a significant contribution to electronics organizations in evaluation and selection of third party RL partner while achieving efficiency and effectiveness in RL practices.

Keywords: MCDM; Reverse logistics (RL); Fuzzy AHP; Fuzzy TOPSIS; Sensitivity analysis (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (10)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:recore:v:108:y:2016:i:c:p:63-81

DOI: 10.1016/j.resconrec.2015.12.011

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